PROJECT SUMMARY The goal of this project is to determine the contribution of hemodynamic factors to risk assessment of unruptured intracranial aneurysms (UIAs) and calculate these factors from enhanced in vivo 4D flow MRI data. Even though most UIAs are stable, the majority of UIA patients are offered interventional treatment due to the grave risk presented if an aneurysm ruptures. Previous studies indicated that in addition to clinical (e.g., age, sex, comorbidities) and morphological (e.g., location and size) factors, UIA progression is affected by local blood flow dynamics. Hemodynamic factors associated with UIA growth can be obtained from computational and experimental models or from 4D flow MRI measurements; however, each approach has limitations. The previous NIH-funded project focused on developing image-based computational methods for predicting postoperative flow following interventions. The goal of this renewal is to use the developed framework to improve risk stratification of UIAs using image-based flow analysis. The proposed project will develop multi-parametric predictive models that combine clinical and morphological factors with hemodynamic factors calculated from augmented 4D flow MRI data. The UIA growth predicted by different models will be compared to outcomes observed in longitudinal imaging studies. The aims of the proposed project are, therefore, to: (1) determine the probability of UIA growth by utilizing morphological and clinical factors together with hemodynamic factors obtained from computational and experimental flow models by a) performing statistical analysis based on morphological and clinical factors obtained from longitudinal imaging, and b) extending statistical model by including hemodynamic factors computed from patient-specific models; (2) Enhance 4D flow MRI data by a) determining 4D flow reproducibility and variability with in vitro studies, and b) applying advanced data augmentation methods to improve the accuracy of calculated hemodynamic factors affecting aneurysm growth; (3) determine the probability of UIA growth based on multi-parametric analysis utilizing hemodynamic factors calculated from enhanced 4D flow MRI. Successful completion of the project will resolve the controversy regarding how hemodynamic factors affect aneurysm growth and establish 4D flow MRI as a diagnostic tool for UIA risk stratification. This collaborative project engages the cardiovascular engineering group at Purdue University and neurosurgeons, neuroradiologists and MRI physicists at Northwestern University, University of California San Francisco and Barrow Neurological Institute. This cross-disciplinary team will bring together experts in neurovascular surgeries, MRI velocimetry, patient-specific flow computations, experimental fluid mechanics and statistical analysis. Retrospective and prospective UIAs data obtained from these superb clinical centers will be used in this study. The outstanding engineering resources available at Purdue and world-class imaging resources at Northwestern, UC San Francisco and Barrow, as well as existing the data sharing agreements between these institutions and ongoing collaborations between the PIs, will ensure the project's success.